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--- aira:start [2025/11/12 14:53] – [Schedule Autumn 2025] mzk
+++ aira:start [2025/11/12 14:53] (current) – [2025-11-06] mzk
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+==== 2025-11-13 ====
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+**Speaker**: Tomáš Kliegr with the research team @ Prague University of Economics and Business
+**Title**: RAG research, LLMs as digital twins, Rule Learning in relational data - perspectives in AI Research .
+**Abstract**:
+- Mateusz Ploskonka: RAG Research Presentation - Mateusz will present a comprehensive empirical evaluation of 32 LLMs (from 0.6B to 1T parameters) across various Retrieval-Augmented Generation (RAG) configurations. His research challenges the ""bigger is better"" assumption by identifying a critical performance plateau at 30B parameters, offering evidence-based guidance for practitioners to balance answer quality, cost, and sustainability in production RAG deployments.
+- Barbara Moreová: LLMs as digital twins for simulating effect of cognitive biases - Barbara will present her research on using Large Language Models to create digital twins for the simulation of human cognitive biases.
+- Kateřina Hrudková: Rule Learning in Relational Data: Methods, Interoperability, and Bioscience Applications -  Kateřina’s research bridges the gap between expressive Inductive Logic Programming (ILP) and scalable RDF rule learners. She will present tools (popper2rdf, rdf2popper) that enable this interoperability and demonstrate a practical application using the RDFRules system to discover interpretable ""nuggets"" from large-scale biomedical knowledge graphs, aiding in tasks like drug repurposing for COVID-19 and classifying microbial media.
+**Biogram**:
+Tomáš Kliegr is a Professor at the Faculty of Informatics and Statistics at the Prague University of Economics and Business (VSE Praha), where he is part of the Data Science & Explainable AI (DSXAI) research team. His research interests include Explainable AI (XAI), Interpretable Machine Learning, and neurosymbolic methods. He has published on topics such as the effect of cognitive biases on model interpretation in journals including Artificial Intelligence and Machine Learning. He is active in the rule-based systems community.
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 ==== 2025-11-06 ====